Proceeding of the Faculty of technical Sciences, Novi Sad

Electrotechnical and Computer Engineering

Vol. 41 No. 08 (2026): Proceedings of the Faculty of Technical Sciences

Filtering in industrial systems: comparative study and implementation in a software oscilloscope

  • Andjela Lakic
DOI:
https://doi.org/10.24867/
Submitted
September 7, 2026
Published
2026-09-09

Abstract

This paper presents a comparative study of filtering techniques for industrial automation and their implementation in the KeStudio Scope software oscilloscope by KEBA. Three filter groups are analyzed: IIR filters (Butterworth, Chebyshev I and II), adaptive filters (LMS, NLMS, RLS), and nonlinear filters (Kalman, EKF, UKF, SIR particle filter). Results demonstrate that Chebyshev II achieves the best performance for stationary signals, RLS for adaptive applications, while SIR particle filter provides the most accurate results for nonlinear systems. Based on the analysis, a hybrid solution combining NLMS and particle filter was implemented. 

References

  1. [1] M. Shouran and E. Elgamli, "Design and
  2. implementation of Butterworth filter," *Int. J. Innov.
  3. Res. Sci. Eng. Technol.*, vol. 9, pp. 7975, 2020.
  4. [2] M. Chavan, R. Agarwala, and M. Uplane,
  5. "Comparative study of Chebyshev I and Chebyshev II
  6. filter used for noise reduction in ECG signal", Jan.
  7. 2008.
  8. [3] J. Okoekhian, M. Guiawa, and I. Onyegbadue,
  9. "Design and simulation of adaptive filters in real-time
  10. environment," *Int. J. Res. Rev.*, vol. 11, no. 11, pp.
  11. 215–238, 2024. doi: 10.52403/ijrr.20241118.
  12. [4] J. Benesty and T. Gänsler, "New insights into the RLS
  13. algorithm," *EURASIP J. Adv. Signal Process.*, vol.
  14. 2004, no. 3, p. 243857, 2004. doi:
  15. 10.1155/S1110865704310188.
  16. [5] A. Kutschireiter, S. C. Surace, and J.-P. Pfister, "The
  17. hitchhiker’s guide to nonlinear filtering," *J. Math.
  18. Psychol.*, vol. 94, p. 102307, 2020. doi:
  19. 10.1016/j.jmp.2019.102307.